Description: Quasi-structured data is a type of information that does not conform to a rigid schema like structured data but still possesses certain organizational properties that allow for analysis and processing. Unlike completely unstructured data, such as free text or images, quasi-structured data contains tags or markers that facilitate the identification of its content and structure. This makes it an intermediate category that combines the flexibility of unstructured data with some organizational characteristics of structured data. A common example of quasi-structured data is JSON and XML files, which allow for the representation of data in a readable and hierarchical format, but without the rigidity of a relational database. This flexibility is especially valuable in environments where data may change frequently or where rapid integration of different information sources is required. In data engineering, handling quasi-structured data is crucial for creating systems that can adapt to the variability of data in real-time, thus facilitating informed decision-making and analysis of large volumes of information.
History: The concept of quasi-structured data began to gain relevance in the 1990s with the rise of the web and the development of technologies such as XML (Extensible Markup Language), which allowed for more flexible data representation. As web applications and online services proliferated, the need to handle data that did not fit into rigid schemas became evident, leading to the adoption of formats like JSON (JavaScript Object Notation) in the 2000s. These formats facilitated interoperability between different systems and the integration of data from various sources, driving the growth of data engineering and the analysis of large volumes of information.
Uses: Quasi-structured data is used in a variety of applications, especially in the field of data engineering and information analysis. They are common in the development of APIs (Application Programming Interfaces), where a flexible format is required to exchange data between different systems. They are also used in web content management, where data may vary in structure and format. Additionally, they are essential in analyzing data from social networks, where information can be diverse and not follow a predefined schema.
Examples: Examples of quasi-structured data include JSON files used to exchange information between web applications, XML documents that describe the structure of data in web services, and CSV data that, while having a tabular structure, can contain fields with varied and non-uniform information. Another example is emails, which have a defined format but can include free text and attachments of different types.
